NoContactNoWorries: Estimating Contact through Vision and Proprioception for In-Hand Dexterous Manipulation
arXiv:2606.24450v1 Announce Type: cross Abstract: Perceiving physical contact is fundamental to dexterous manipulation. While robots often rely on dedicated hardware tactile sensors, humans exhibit a remarkable ability to infer contact by integrating visual information with an innate sense of their body's pose and movement. Inspired by this embodied perceptual skill, we investigate whether a robot can learn to infer contact from vision, an approach that also offers a scalable alternative to tactile hardware specifically for binary contact estimation, which faces practical challenges in cost, f
The proliferation of advanced AI techniques and improved sensor fusion capabilities allows for a more sophisticated approach to robot perception, moving beyond hardware-centric solutions.
This research enables robots to infer contact more adaptively and cost-effectively, reducing reliance on expensive and fragile tactile sensors, which is crucial for scaling dexterous manipulation in unstructured environments.
Robots can now potentially achieve dexterous manipulation with less specialized hardware, making advanced robotics more accessible and robust for real-world applications.
- · Robotics manufacturers
- · Logistics and manufacturing sectors
- · AI software developers
- · E-commerce
- · Manufacturers of solely hardware-based tactile sensors
- · Companies reliant on highly controlled robotic environments
Robots will become more versatile in handling varied objects without prior programming for specific contact conditions.
This improved dexterity will accelerate the adoption of robots in tasks traditionally considered too complex or delicate for automation.
A wider deployment of dexterous robots could lead to new forms of human-robot collaboration and service industries.
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Read at arXiv cs.AI